Jamie E 23 Jun 2023 14:06 UTC
33 points
3 ∶ 1
in reply to: Sarah Levin’s comment on: How has FTX’s collapse affected public perception of EA?
We can get a better intimation of the magnitude of the effect here with some further calculations. If we take all the people who have pre and post FTX satisfaction responses (n = 951), we see that 4% of them have a satisfaction score that went up, 53% remained the same, and 43% went down. That’s quite a striking negative impact. For those people whose scores went down, 67% had a reduction of only 1 point, 22% of 2 points, and then 7%, 3%, and 1% each for −3, −4, and −5 points.
We can also try to translate this effect into some more commonly used effect size metrics. Firstly, we can utilise a nice summary effect size metric for these ratings known as probability of superiority (PSup), which makes relatively few assumptions about the data—mainly that higher ratings are higher and lower ratings are lower, within the same respondent. This metric summarises the difference over time by taking the proportion of cases in which a score was higher pre-FTX (42.7%), and assigning a 50% weight to cases in which the score was the same from pre to post FTX (.5 * 53.2% = 26.6%), and adding these quantities together (69.3%). This metric is taken as an approximation of the proportion of people who would report being more satisfied before vs. after in a forced choice of being more or less satisfied. If everyone was more satisfied before, PSup would be 100%, if everyone was more satisfied after, PSup would be 0, and if it were just as likely for people to be more or less satisfied before or after, PSup would be 50%. In this case, we get a PSup of 69.3%. This corresponds to an effect size in standard deviation units (like Cohen’s d), of approximately .7.
We would encourage people not to just look up whether these are small or large effects in a table that would say e.g, from wikipedia, that .7 is in the ‘medium’ effect size bin. Think about how you would respond on this kind of question, what a difference of 1 or more points would mean in your head, and what precisely you think the proportions of people giving different responses substantively might mean to them. How one can best interpret effect sizes varies greatly with context

Pulse 2024: Public attitudes towards charitable cause areas

Jamie E27 Nov 2024 11:32 UTC

29 points

0 comments4 min readEA link

Jamie E 27 Mar 2023 9:20 UTC
17 points
1 ∶ 0
on: On what basis did Founder’s Pledge disperse $1.6 mil. to Qvist Consulting from its Climate Change Fund?
For some further information on Qvist’s background, you could also check out his google scholar page: https://scholar.google.com/citations?hl=en&user=JFopkowAAAAJ&view_op=list_works&sortby=pubdate
Two 2022 papers have ‘repowering coal’ in the title so presumably might have some further background on the strategy or basis of these ideas, though I did not check them out myself:
Repowering a Coal Power Unit with Small Modular Reactors and Thermal Energy Storage
Repowering Coal Power in China by Nuclear Energy—Implementation Strategy and Potential

Jamie E 12 May 2023 15:17 UTC
15 points
2 ∶ 0
on: US Supreme Court Upholds Prop 12!
Pretty funny in the opinion!:
“under this Court’s dormant Commerce Clause decisions, no State may use its laws to discriminate purposefully against out-of-state economic interests. But the pork producers do not suggest that California’s law offends this principle. Instead, they invite us to fashion two new and more aggressive constitutional restrictions on the ability of States to regulate goods sold within their borders. We decline that invitation. While the Constitution addresses many weighty issues, the type of pork chops California merchants may sell is not on that list.”

Jamie E 5 Sep 2023 8:52 UTC
14 points
6 ∶ 0
on: The Plant-Based Universities open letter has now gone public
“This is undoubtedly a massive opportunity to kickstart positive change at a large institutional scale with minimal cost or risk involved” … “The primary motivation of this campaign may be for universities to limit their contribution to climate change and to shift public opinion in favour of a plant-based food system”
Although I’m supportive of moves towards plant-based diets and better plant-based options being available, I wonder how confident one can be that this is truly minimal risk, especially with regards to the stated goal of shifting public opinion in favour of plant-based food systems. Do we know what proportion of students would really favour not have access to non-plant-based foods on campus (representative data, rather than petitions etc.)? If a majority are in favour, could this kind of action produce a very disgruntled minority who feel these things are being forced upon them and are resistant for the remainder of their lives to similar or other forms of animal advocacy. I’d be interested to know if there is any data/other relevant information or discussion with respect to these possible risks, and the popularity of such changes among the whole student body

Jamie E 4 Nov 2022 13:07 UTC
9 points
3 ∶ 0
on: Righting past wrongs by recovering past lives via simulation
At a philosophical level, I don’t really find it very convincing that even a perfect recovery/replica would be righting any wrongs experienced by the subject in the past, but I can’t definitively explain why—only that I don’t think replicas are ‘the same lives’ as the original or really meaningfully connected to them in any moral way. For example, if I cloned you absolutely perfectly now, and then said, I’m going to torture you for the rest of your life, but don’t worry, your clone will be experiencing eqaul and opposite pleasures, would you think this is good (or evens out) for you as the single subject being tortured, and would it correct for the injustice being done to you as a subject experiencing the torture? All that is being done is making a new person and giving them a different experience to the other one.

Jamie E 22 Nov 2024 11:32 UTC
8 points
2 ∶ 0
on: LLM chatbots have ~half of the kinds of “consciousness” that humans believe in. Humans should avoid going crazy about that.
I am skeptical that the evidence/examples you are providing in favor of the different capacities actually demonstrate those capacities. As one example:
“#2: Purposefulness. The Big 3 LLMs typically maintain or can at least form a sense of purpose or intention throughout a conversation with you, such as to assist you. If you doubt me on this, try asking one what its intended purpose is behind a particular thing that it said.”
I am sure that if you ask a model to do this it can provide you with good reasoning, so I’m not doubtful of that. But I’m highly doubtful that it demonstrates the capacity that is claimed. I think when you ask these kinds of questions, the model is just going to be feeding back in whatever text has preceded it and generating what should come next. It is not actually following your instructions and reporting on what its prior intentions were, in the same way that person would if you were speaking with them.
I think this can be demonstrated relatively easily—for example, I just made a request from Claude to come up with a compelling but relaxing children’s bedtime story for me. It did so. I then then took my question and the answer from Claude, pasted it into a document, and added another line: “You started by setting the story in a small garden at night. What was your intention behind that?”
I then took all of this and pasted it into chatgpt. Chatgpt was very happy to explain to me why it proposed setting the story in a small garden at night.

Jamie E 20 Aug 2024 17:56 UTC
8 points
1 ∶ 0
on: Explicit Ethics
I think part of the concern is that when you try to make ethics explicit you are very likely to miss something, or a lot of things, in the ‘rules’ you explicitly lay down. Some people will take the rules as gospel, and then there will also be a risk of Goodharting.
In most games there are soft rules beyond the explicit rules that include features that are not strictly part of the game and are very hard to define, such as good sportsmanship, but really are a core part of the game and why it is appreciated. Many viewers don’t enjoy when a player does something that is technically allowed but is just taking advantage of a loophole in the explicit rules and not in the spirit of the game, or misses the point of the game (an example from non-human game players is that AI speedboat that stopped doing the actual race and starts driving round in circles to maximise the reward. We like it as an example of reinforcement learning gone wrong, but it’s not what we actually want to watch in a race). People who only stick to the exactly explicit laws tend to be missing something/be social pariahs who take advantage of the fact that not all rules are or can be written down.